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911 articles for “Integrated modeling”
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Development and Performance Evaluation of Hybrid Solar Water Heating and Distillation Systems for Sustainable Water Supply: A Comprehensive Review
Abstract: This review article delves into the comprehensive examination of hybrid solar water heating and distillation systems, underscoring their pivotal role in addressing global water and energy challenges. With the increasing scarcity of clean water and the growing demand for sustainable energy solutions, these hybrid systems offer a promising dual-purpose approach. The article synthesizes the latest advancements in technology, design methodologies, and performance evaluation metrics, providing a holistic view of the …
Published in Recent Trends in Fluid Mechanics · Vol. 11, Issue 1, 2024 · pp. 8–19 Read article
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Quantum Error Correction on Cryptography
Abstract: This article introduces novel concepts in quantum error correction and cryptography. It explores “approximate quantum error correction” (AQEC), which relaxes the requirement for perfect error correction in quantum systems. AQEC specializes in creating codes tailored to specific types of noise models. The study establishes a universal, near-optimal recovery map for AQEC, simplifying the identification of effective approximate codes. In the realm of noisy-storage cryptography, the research envisions secure two-party cryptographic …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 18–23 Read article
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VLSI Based Traffic Light Controller
Abstract: This study details the development and realization of an advanced traffic light control system utilizing VHDL (Very High-Speed Integrated Circuit Hardware Description Language) in conjunction with FPGA (Field Programmable Gate Array) technology. The system is designed to regulate a four-way intersection, with one primary high-traffic road intersecting with a less congested side road. To enhance traffic efficiency and minimize idle times, the model incorporates intelligent features such as a vehicle …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 2, 2025 · pp. 40–47 Read article
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Transforming Rare Disease Diagnosis with AI
Abstract: Artificial intelligence is changing healthcare fast. It is making diagnoses accurate, helping doctors get better results, and streamlining how care works. This paper looks at how AI shows up in healthcare right now – where it is already making a difference, what is working, and what is still tricky. The focus is on machine learning, natural language processing, and computer vision. Particular attention is given to using AI in diagnosing …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
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Structure–Property Correlation of Infill Topology and Density on Tensile and Flexural Performance of FDM-Printed PLA and ABS
Abstract: Additive Manufacturing (AM), particularly Fused Deposition Modeling (FDM), has become a widely adopted manufacturing technology due to its design flexibility, low cost, and capability for rapid prototyping. However, the mechanical performance of FDM-printed components is strongly influenced by internal structural parameters such as infill pattern and infill density, in addition to the intrinsic material behaviour. This study investigates the structure–property relationship between infill topology, density, and mechanical performance of PLA …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 4, Issue 1, 2026 · pp. 26–37 Read article
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Integrative Machine Learning Approaches for Predicting the Rheological Behaviour of Soft Magnetorheological Elastomers
Abstract: Magnetorheological Elastomers (MREs) are advanced composite materials known for their ability to alter mechanical properties under external magnetic fields, making them highly valuable in adaptive damping systems, vibration control, and smart devices. The accurate prediction of rheological behavior in soft MREs remains a significant challenge due to the complex interplay between material composition and magnetic fields. To address this challenge, this study employs a multi-pronged approach that integrates traditional material …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1083–1096 Read article
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Design and Analysis of G+4 Building with Ductile Detailing
Abstract: This study presents the structural design and analysis of a G+4 residential building, with a specific focus on ductile detailing to enhance seismic performance. Ductility plays a crucial role in enabling structures to absorb and dissipate energy during seismic events, thereby minimizing structural damage and improving safety. The project emphasizes key reinforcement strategies such as beam-column junction detailing and confining reinforcement, which are critical to preventing brittle failures and improving …
Published in Journal of Structural Engineering and Management · Vol. 12, Issue 2, 2025 · pp. 1–9 Read article
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A Review on Two-Wheeled Self-Balancing Robot Using Spartan-3E FPGA for Sensor Fusion and Real-Time Motor Control
Abstract: Two-wheeled self-balancing robots (TWSBR) are a popular application of embedded control and robotics because they operate on the inverted pendulum concept, which is naturally unstable. The main objective of such robots is to continuously maintain balance by estimating the tilt angle and applying corrective motor action in real time. In most practical systems, low-cost inertial sensors such as accelerometers and gyroscopes are used for tilt measurement. However, accelerometer readings are …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 1, 2026 · pp. 17–27 Read article
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AI Voice Detection Tool
Abstract: In today’s digital era, distinguishing between AI-generated and human voices is more important than ever. This project introduces an AI-based voice detection system designed to accurately identify synthetic voices, ensuring security and authenticity across various applications like cybersecurity, media verification, and fraud prevention.Our system works by analyzing incoming audio samples and comparing them against a diverse database of both AI-generated and real human voices. Using advanced machine learning and signal …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 1, 2026 · pp. 1–8 Read article
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Mapping A Contextualized Southern Africa's Innovation Ecosystem: The Emerging Role of Higher Education in Promoting Inclusive Innovation and Rural Industrialization
Abstract: Higher education institutions (HEIs) are increasingly recognized as strategic actors in shaping innovation ecosystems that can respond to persistent socio-economic inequalities in the Global South. In Southern Africa, where rural underdevelopment, youth unemployment, weak industrial bases, and uneven innovation capacities remain pressing concerns, universities are under growing pressure to move beyond their traditional teaching and research mandates and contribute more directly to inclusive development. This paper examines the emerging role …
Published in International Journal of Rural and Regional Development · Vol. 4, Issue 1, 2026 · pp. 14–27 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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AI-Assisted Gain Scheduling for Real-Time Temperature Control in Chemical Reactors
Abstract: Temperature control in continuous stirred-tank reactors (CSTR) represents a critical challenge in chemical process industries due to inherent nonlinearities, time-varying dynamics, and parametric uncertainties. Conventional proportional-integral-derivative (PID) controllers with fixed gains often fail to maintain optimal performance across varying operating conditions, leading to temperature excursions that compromise product quality and safety. This paper presents a novel AI-assisted gain scheduling framework that integrates artificial neural networks (ANN) with adaptive PID control …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 24–33 Read article
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Damage Evolution and Delamination Resistance in Polymer Matrix Functionally Graded Laminates
Abstract: Functionally graded laminates (FGLs) in polymer-matrix systems represent a promising pathway to enhance damage tolerance and delay delamination in advanced structural composites. In this study, we explore the mechanisms of damage initiation, propagation, and delamination resistance in polymer matrix functionally graded laminates (PM-FGLs) through a combined experimental–computational approach. Laminates with linear, exponential, and bio-inspired gradation profiles were fabricated using vacuum-assisted resin transfer molding (VARTM) and additive manufacturing techniques. Comprehensive mechanical …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 321–337 Read article
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Low-Weight, High-Durability Crankshaft Development Using Glass Fiber Composites: Numerical and Experimental Investigations
Abstract: The present paper aims towards the weight reduction of crankshaft by replacing conventional medium carbon steel for a two-wheeler with composite material. The replacement is such that it significantly reduces load on other components without compromising structural integrity. It will also serves in terms of operating reliability or durability over its life span. A geometric specifications and dimensions were obtained using a 3D CAD model developed in CATIA V5. The …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Advancements in Humanoid Robot Locomotion: A Review of Control Strategies and Kinematic Models
Abstract: Humanoid robot locomotion has significantly improved over the past few decades, driven by improvements in control strategies and kinematic models. Researchers aim to develop robots that can walk, run, and navigate complex terrains with efficiency and stability. This review explores recent developments in humanoid locomotion, highlighting control strategies such as model predictive control, reinforcement learning, and central pattern generators. Additionally, it examines kinematic models, including inverted pendulum models and zero …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 1, 2025 · pp. 24–30 Read article
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AquaSential: Autonomous UAV-Based Water Quality Monitoring System
Abstract: The increasing occurrence of waterborne health risks and the presence of harmful microorganisms in freshwater environments highlight the need for rapid and continuous water quality monitoring. Traditional laboratory-based testing methods often require significant time and manual sampling, limiting their ability to provide immediate information about changing environmental conditions. This work presents AquaSential, a low-cost, portable, and UAV-ready water quality monitoring system designed for real-time assessment of freshwater bodies. The proposed …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 2, 2026 Read article
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Design of an Integrated Health Monitoring System on an IoT-Based Framework
Abstract: With the advent of industrialization, health ailments have become a major cause of concern owing to an inactive and fast lifestyle, polluted environments, and detrimental eating habits. However, IoT has become a boon for the health sector and humanity on account of its countless benefits, rendering improved quality of service and patient-centric care. An Integrated Health Monitoring System (IHMS) is presented in this paper. This new IoT-based framework integrates wearable …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 1–7 Read article
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Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
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Use of Artificial Intelligence to Access and Ensure Safe Drinking Water Supply: A Review
Abstract: Ensuring access to safe drinking water is a critical public health challenge. Traditional water quality assessment methods are often labor-intensive and time-consuming. Artificial intelligence offers a promising alternative, providing rapid, accurate, and scalable solutions for monitoring and predicting water quality. This systematic review examines the application of AI. The review highlights various AI models, including artificial neural networks, support vector machines, decision trees, and ensemble methods, in predicting water quality …
Published in Journal of Water Resource Engineering and Management · Vol. 11, Issue 2, 2024 · pp. 21–28 Read article
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Artificial Intelligence in Cybersecurity: Emerging Trends, Technological Advancements, and Future Directions for Cyber Defense
Abstract: Artificial Intelligence (AI) is revolutionizing the field of cybersecurity by automating complex security tasks, improving threat detection capabilities, and enhancing the precision of threat response mechanisms. With the rapid evolution of cyber threats such as malware, ransomware, phishing, and data breaches, conventional security systems are often insufficient to provide timely and accurate protection. AI, powered by machine learning algorithms and neural networks, enables the analysis of vast datasets to detect …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 103–112 Read article